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@@ -326,6 +326,7 @@ Real numbers from real machines, stock build (`setup.sh`, gcc 13), greedy decodi
 | Ryzen 9 9950X (32 threads) · Linux · 123 GB · Crucial P3 QLC Gen3 ([#31](https://github.com/JustVugg/colibri/issues/31)) | 1.51 GB/s buffered | default, 2 runs from cold | 0.10 tok/s · hit 53% · profile 66% disk |
 | 〃 same machine, model moved to a Samsung 9100 PRO PCIe 5.0 ([#31](https://github.com/JustVugg/colibri/issues/31)) | **8.81 GB/s** O_DIRECT | 〃 (usage history retained) | **0.28 tok/s** · hit 57% · profile flips: 32% disk / **57% matmul** |
 | Ryzen AI Max+ 395 (Framework Desktop) · Ubuntu · 128 GB LPDDR5x · Intel Optane 905p PCIe 3.0 ([#39](https://github.com/JustVugg/colibri/issues/39)) | 3.27 GB/s buffered | int8 MTP head · fresh history (pure LRU, auto-raised cap 65) | 0.16 tok/s · hit 57% · profile 49% disk / 47% matmul |
+| 〃 five runs later — learned pin 47.6 GB ([#39](https://github.com/JustVugg/colibri/issues/39)) | 〃 | `--temp 0.7 --topp 0.7` | **0.40 tok/s** · hit 71% · fastest non-Apple datapoint |
 
 Takeaways: with 24 GB of RAM the engine auto-caps the expert cache to 2 slots/layer, so decode stays cold even on a disk 2–2.7× faster than the dev box — **on small-RAM machines the RAM cap, not the disk, is the binding constraint**, exactly as the table above predicts; `--topp 0.7` alone bought a clean 1.6× end-to-end speedup. The M5 Max datapoint lands right on the table's second row: **~1 tok/s of a 744B model on a laptop SSD** — and its 14 GB/s disk shifts the bottleneck back to RAM budget and kernels. The Framework 13 rows are the cache thesis proven end-to-end on one machine: 0.29 → 0.37 tok/s (hit 28% → 66%, speculation finally engaging at 52% acceptance) just by giving the cache its RAM — int8 MTP head + a bigger cap + the learned pin. The cap part is now automatic (cap auto-raise, 2026-07-10). The 9950X pair is the cleanest bottleneck experiment yet — same machine, same history, only the disk swapped: ×5.8 disk bandwidth bought ×2.9 tokens, and the profile **flipped from 66% disk to 57% matmul**. Past ~5 GB/s the disk stops being the story and the CPU (or the CUDA expert tier) becomes it.